Reuben Baris, Michael Barrett, Rochelle Bohaty , Marietta Echeverria, Ian Kennedy (PMRA), Greg Malis (PMRA), James Wolf, Dirk Young

Exposure Modeling Public Meeting

March 20, 2012

1 A North American Free Trade Agreement project: U.S. Environmental Protection Agency & Health Canada

# US EPA Model Guidance

Unique Qualities of Regulatory Models

- Transparency

- Non Proprietary

http://www.epa.gov/crem/library/cred_g uidance_0309.pdf

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# US EPA Quality Assurance Guidance

Combination of G - 5M and CREM Guidance

3

# General Steps to Produce a 

# Regulatory Model

 

### Conceptual Model Development

 

### Implementation

 

### Evaluation

 

### Application

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# Evaluation

 

### “The process used to generate information that will determine whether a model and its analytical results are of a sufficient quality to inform a decision.” (CREM)

INCLUDES:

 

### Verification

- Model Code Check

 

### Validation

 

### Data Corroboration

– CREM

- preferred term

 

### Peer Review

– used throughout the process

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# Application

 

## Internal evaluation by Tech Teams

 

## Review of acceptability of evaluation

 

## Creation of plan for use in assessments

 

## Management review

 

## Communications Officer review

 

## Final approval by Division Director

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# Groundwater Conceptual Model

Hydrolysis or other relevant processes below 1m Depth to aquifer Declining aerobic degradation with depth 1 m

Well Screen Length Potable well drawing from surficial aquifer

Water Table

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# Implementation of the 

# Conceptual Model

 

### Reviewed 19 models

 Capabilities, ease of use, maintenance, proprietary state



###  

### Intense evaluation of PRZM, LEACHP, and PEARL

 Performance checks, user issues



###  

### Selected PRZM for more evaluations

 

### Developed User interface for PRZM

- GW

8 PRZM: Pesticide Root Zone Model; LEACHP: Leaching Estimation and Chemistry Model; PEARL: Pesticide Emission Assessment at Regional and Local Scales

# PRZM

- GW User Interface

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# QA Objectives for Evaluation

 

### Data Quality Objective

 Non

- targeted Data: Groundwater simulations should not be below those observed in the test studies

 Targeted studies where use data is known : Groundwater simulations should be similar to those observed in the test studies

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# Monitoring Data
Non

- targeted data

 

### U.S. Geological Survery , National Water Quality Assessment Program (USGS NAWQA) 

### Semi

- targeted Study:

 

### National Alachlor Well

- Water Survey (NAWWS) Targeted Studies

 

### Prospective Groundwater Monitoring (PGW) study

 

### U.S. Dept. of Ag., Pesticide Data Program 

### (USDA PDP) data from California

 

### Acetochlor Registration Partnership Midwest Corn Production Area (ARP/ MwCPA Program) 11

# Non
- targeted Evaluation: NAWQA Data and Maximum Use PRZM

- GW Screen Simulated Concentrations

Observed Concentrations 12

# Semi
- targeted: National Alachlor Well

- Water Survey (NAWWS)

 

### Existing private drinking water wells down gradient of agricultural fields

 

### History of use for alachlor , atrazine , metolachlor

 

### PRZM

- GW, when conservatively parameterized as a screen, produces conservative estimates

Holden et al . (1988, 1992), and Liddle et al. (1990) 13

# Targeted Evaluation: Prospective Groundwater Study with Known Use

PGW Max = 4.55 ppb

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# Targeted Evaluation : PDP Diuron

2590 ppb Screen: Hydrolysis is stable Soil Degradation= 1116 days Max Label Rate = 8.96 kg/ hA Refinement: Hydrolysis = 1240 days Soil Degradation = 372 days Actual Rate = 0.31 kg/ hA Diuron Measured Value = 0.123 ppb

Reduction Factors Hydrolysis = 70 Soil Degradation= 5.9 Label Rate = 30 0.278 ppb

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# Targeted Evaluation: Acetochlor Registration Partnership Mid

- Western Corn Production Area (ARP

- MwCPA )

Chemical Monitoring Peak 

### (ppb) PRZM

– GW 

### (Refined) Acetochlor 0.74 0.99 Alachlor 15.59 18.17 Atrazine 7.76 46.76 Metolachlor 5.98 2.92

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# Peer Review

 

### SAP * 

### February 2005

 

### August 2005

 

### EMPM (several 2005 to 2010)

 

### User comments

17 * Scientific Advisory Panel

# Summary

 

### With known pesticide use & good fate input parameters, PRZM

- GW does well

 

### When maximum labeled rates are used, minimum treatment intervals, and annual application events, PRZM

- GW provides conservative estimates of GW concentrations

 

### PRZM

- GW is still in the evaluation phase

 

### Currently developing plan for consistent use in EFED assessments 18

# References

Holden, L.R., J.A. Graham, R.W. Whitmore, W. J.. Alexander, R.W. Pratt, S.K. Liddle , L.L. Piper. 1992. Results of the National Alachlor Well Water Survey. Environmental Science & Technology 26 (5), 935

- 943. Liddle , S. K., R. W. Whitmore, R. E. Mason, W. J. Alexander, and L. R. Holden. 1990. Accounting for temporal variations in large

- scale retrospective studies of agricultural chemicals in ground water. Ground Water Monitoring Review. Winter, pp. 142

- 145. Holden, L.R., R.W. Whitmore, and l.A . Graham. 1988. The national alachlor well water survey: Statistical design and current status. In Proceedings of the Agricultural Impacts on Ground Water Conference, National Water Well Assoc. Des Moines, Iowa. pp. 237

- 254. USEPA CREM Guidance for Developing Regulatory Models: http://www.epa.gov/crem/library/cred_guidance_0309.pdf

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